Increasingly, enterprises are seeking to improve the productivity of employees who must find valuable information. Existing search and recommendation systems help users to find information content relevant to user queries or profiles. Such existing search and recommendation systems often rank documents using a score based on the number of links among documents. Enterprise documents, however, such as enterprise forms and manuals, often do not contain links. Thus, existing search systems do not perform well for employees searching enterprise documents, such as material that will allow the employee to increase his or her productivity.
To help employees find valuable information that improves their productivity, a comprehensive understanding is required of the intrinsic characteristics of information content within enterprises and how this is related to worker productivity. To this end, recent empirical work has started to capture people's electronic communications (e.g., email, text messaging, and document repositories) as well as productivity metrics (e.g., revenues and performance ratings). In particular, such electronic communications data have the advantage of wide coverage and minimal need of human involvement.
Based on the personal relationships revealed by the captured data, research has shown the benefit of social networks on information worker productivity within an organization. See, for example, S. Aral et al., “Information, Technology and Information Worker Productivity Task Level Evidence,” Proc. of the 27th Annual Int'l Conf. on Information Systems (2006); or L. Wu et al., “Value of Social Network—A Large-Scale Analysis on Network Structure Impact to Financial Revenue of Information Technology Consultants,” Winter Conf. on Business Intelligence (2009). Most existing studies, however, focus on social network topologies and node properties. There is little, if any, research investigating the correlation between productivity and the ample yet diverse information content created by people's communications.
In particular, existing research does not explain how content can impact information workers' productivity, an issue especially important to enterprises. For example, a “hot” topic mentioned frequently by many people may appeal to the personal life of an employee, but may not improve his or her productivity. Thus, a need still exists for methods and apparatus for discovering valuable topics in an enterprise environment, such as information to improve worker productivity. Yet another need exists for methods and apparatus that rank information content by value to productivity by mining the relationship among people's productivity data (e.g., financial performance), generated information content and social network.